Top Object-Oriented Programming Languages You Should Know

Last Updated: December 08, 2025

Object oriented programming languages shape a large part of modern software development. They support clear structure, predictable behavior, and strong code organization. Many companies use them for applications that need stability and long-term maintenance. This helps development teams work faster and reduce technical debt.

S3Corp works with global clients that rely on these languages to build scalable and future-ready systems. This guide explains what OOP is, how OOP concepts work, and which object oriented programming languages stand out today.

What Are Object-Oriented Programming Languages?

Object oriented programming languages follow a simple idea: you build software by grouping data and functions into structured units called objects. These objects act like real items. A user, an invoice, a product, or a vehicle can all be objects with clear behavior.

The purpose of OOP programming languages is to create code that developers can organize, reuse, update, and maintain with less effort. This approach supports large projects that run for many years. It also supports small projects that grow over time.

Here's a quick example. Imagine you're building a car rental system. You'd create a Car class that defines properties like color, model, and year. Then you'd create individual car objects from that class—a red Toyota, a blue Honda, each with its own specific details but following the same blueprint.

Classes serve as templates. Objects are the actual instances created from those templates. A recipe is a class. The cake you bake from it is an object.

This approach mirrors how we naturally think about the world. We categorize things, recognize patterns, and understand that a sports car and a sedan are both cars but with different characteristics. Object oriented languages let programmers code the same way.

Most modern applications use OOP because it handles complexity better than older procedural approaches. When your codebase grows to thousands or millions of lines, having everything neatly organized into objects makes a massive difference. These features explain why object-oriented programming languages remain popular across many industries today.

What Is the Structure of Concepts in Object-oriented Programming?

Object-oriented languages is built on four key components: classes, objects, attributes, and functions. These elements work together to organize and manage data efficiently, making code easier to understand, reuse, and modify. Let’s break them down in detail.

Classes

Think of a class as a template or blueprint. It defines the structure and behavior of objects. Imagine designing a car—before you build one, you need a blueprint that outlines its features like wheels, engine, and seats. In OOP, a class serves this same purpose. It defines what an object should contain, including its attributes (data) and functions (behaviors). Without classes, you’d have to rewrite similar structures repeatedly, making your code inefficient and messy.

For example, if you're developing a game and want multiple player characters, you wouldn’t create each one from scratch. Instead, you’d define a Player class that sets common properties like health, speed, and abilities. Then, you can create different characters (objects) based on this class while giving them unique values for their attributes.

Objects

An object is a real-world example of a class. If the class is the blueprint, the object is the actual product built from it. Suppose you have a Car class with attributes like "color" and "model"—each actual car you create from this class is an object.

Each object has its own unique set of data while following the structure defined by the class.

For example, you can create different car objects:

car1 = Car("Toyota", "Camry", 2022)

car2 = Car("Honda", "Civic", 2023)

Even though both car1 and car2 follow the same Car class structure, they contain different data. This is what makes objects flexible—you can create as many as needed, each with its own unique details.

Objects are self-contained, meaning they store data (attributes) and behaviors (functions) within themselves. This makes it easier to work with multiple objects without interfering with others.

Attributes

Attributes define an object’s state and characteristics. If an object is a character in a game, attributes might include health, strength, or inventory. If it’s a bank account, attributes could be account number, balance, and account holder’s name.

Each object stores its own version of these attributes

Let’s get back to the car example. Attributes like make, model, and year define the characteristics of each car object.

Attributes are often set when an object is created:

class Car:

     def __init__(self, make, model, year):

          self.make = make

          self.model = model

          self.year = year

Here, self.make, self.model, and self.year are attributes assigned to each new car object. Attributes allow objects to store and manage data independently.

Functions

Functions (or methods) inside a class determine what an object can do. They are written inside the class and operate on the object’s attributes. Functions ensure that behavior is tied directly to an object, keeping everything organized.

For instance, a car object might have a function to start its engine:

class Car:

      def start_engine(self):

            print(f"The {self.make} {self.model} engine is now running.")

When you call car1.start_engine(), it will output:

The Toyota Camry engine is now running.

Functions promote reusability and keep code clean by grouping related actions inside the object that uses them.

So, in short, in OOP, classes provide structure, objects bring classes to life, attributes store object data, and functions define object behavior. This approach makes programming more organized and scalable. By grouping related data and functions within objects, OOP ensures that code is more intuitive, modular, and easy to maintain.

4 Pillars Of Object-Oriented Programming

Object oriented programming languages (OOP) enable developers to interact with real-world entities practically. Hence, there are four guiding principles for oop programming languages. These have characteristics that help to distinguish them and enhance their efficiency.

Encapsulation.

Encapsulation is the concept of attaching data to functions that perform a security function to keep that data safe. In this context, objects will contain all critical information. And they will be defined separately as classes. These classes cannot be accessed or modified by any other objects. By doing so, the confidential data of objects will be kept safe and secure from the outside world. Only carefully selected data for public release may be made available.

This data hiding feature helps developers to grasp the code quickly, provides a higher level of security, and prevents unintentional data damage.

Inheritance.

The most common definition of inheritance is an "IS-A" connection in which developers can structure classes into hierarchies. It enables certain classes to function under the form of other ones. A subclass inherits all of the properties and functionalities of its superclass or parent class while still having the potential to extend that capability with additional code and data.

This feature allows developers to minimize unnecessary work by choosing an existing object that already performs well of what is required and reusing code written in other classes.

Abstraction.

In the context of OOP, abstraction is the process of abstracting away the complexities of internal operations and just exposing a user interface that is both clean and simple for the usage of other objects. By hiding any redundant implementation code and focusing on the interface, developers can work more quickly and make further modifications or updates over time. Furthermore, abstraction also benefits the code by isolating the impact of code modifications. As a result, if something goes wrong in the code, the adjustments will only affect the class's implementation details, not the code itself.

Polymorphism.

The term polymorphism refers to the ability to accept more than one shape. In the context of oop programming languages, it refers to the ability to manage objects and take on more than one form based on what they are. In other words, the child objects might not require to react to a query in the same manner as their parent. A new object can replace the methods of its parent by interacting differently with a message. This feature makes coding more flexible, which leads to better code structure in fewer and simpler units.

Best Object-Oriented Programming Languages Today.

Below is an object oriented languages list that covers widely used, high-impact options. Each entry explains what the language is, why developers trust it, and where it fits best. This list includes the top OOP languages used in enterprise systems, web platforms, mobile development, and high-performance applications.

Java

Java remains one of the most widely adopted OOP languages across enterprise environments. Released by Sun Microsystems in 1995, it popularized the "write once, run anywhere" philosophy through its Java Virtual Machine.

The language enforces strong typing and requires everything to exist within classes. There are no standalone functions floating around. This strict structure makes Java code predictable and maintainable across large teams.

Key uses include Android mobile applications, enterprise backend systems, financial services platforms, and large-scale web applications. Banks, insurance companies, and government agencies frequently choose Java for mission-critical systems.

Pros: Extensive libraries, strong community support, excellent documentation, mature ecosystem, high performance after JVM optimization.

Cons: Verbose syntax requires more code for simple tasks, slower startup times, steeper learning curve for absolute beginners.

C#

Microsoft created C# as part of its .NET framework in 2000. The language borrows heavily from Java but integrates tightly with Windows development tools and Azure cloud services.

C# shines in game development through the Unity engine, which powers a significant portion of mobile and indie games. It also dominates Windows desktop applications and enterprise software built on the .NET platform.

Modern C# includes functional programming features alongside OOP, giving developers flexibility in how they structure code. The language continues evolving with regular updates that add contemporary features while maintaining backward compatibility.

Pros: Clean syntax, powerful IDE support through Visual Studio, excellent for game development, strong Windows integration, growing cross-platform capabilities.

Cons: Historically tied to Microsoft ecosystem, smaller community than Java or Python, less common in non-Windows server environments.

Python

Python surprises many beginners when they learn it supports object oriented programming. While you can write procedural Python code, the language fully embraces OOP concepts when needed.

Everything in Python is an object, including numbers, strings, and functions. You just don't always interact with them as objects explicitly. This flexibility makes Python approachable for newcomers while offering depth for complex applications.

Data scientists, machine learning engineers, web developers, and automation specialists all use Python daily. Django and Flask frameworks leverage OOP principles for web development. Libraries like TensorFlow and PyTorch use classes extensively for neural network construction.

Pros: Readable syntax that resembles plain English, massive library ecosystem, excellent for data science and AI, fast development speed, strong community.

Cons: Slower execution than compiled languages, dynamic typing can introduce runtime errors, not ideal for mobile app development.

C++

C++ extends the C programming language with object oriented features while maintaining the performance and low-level control C is known for. Bjarne Stroustrup released the first version in 1985.

The language gives you direct memory management and hardware access, making it the top choice for operating systems, game engines, embedded systems, and high-frequency trading platforms. When milliseconds matter, C++ delivers.

Modern C++ has evolved significantly from its early days. Features like smart pointers, lambda expressions, and move semantics make the language safer and more expressive while preserving its performance edge.

Pros: Maximum performance, fine-grained control over system resources, extensive legacy codebase, supports multiple programming paradigms beyond OOP.

Cons: Complex syntax, manual memory management introduces potential bugs, longer development time, steep learning curve.

Ruby

Ruby emphasizes programmer happiness through elegant, natural syntax. Created by Yukihiro Matsumoto in the mid-1990s, it gained massive popularity with the Ruby on Rails web framework.

Everything in Ruby is an object, even primitive types like integers and booleans. This consistency makes the language feel unified and predictable. Ruby's dynamic nature and metaprogramming capabilities let developers write concise, expressive code.

Web startups frequently choose Ruby on Rails for rapid application development. The framework's conventions reduce decision fatigue and let teams ship features quickly.

Pros: Beautiful, readable syntax, strong convention over configuration philosophy, excellent for web development, supportive community, quick prototyping.

Cons: Slower runtime performance, less common outside web development, smaller talent pool than Java or Python.

PHP

PHP powers a substantial portion of the web, including platforms like WordPress, which runs over 40% of all websites. While PHP started as a procedural language, it added robust OOP support in version 5.

Modern PHP frameworks like Laravel and Symfony rely heavily on object oriented principles. The language has matured significantly, adding features like namespaces, traits, and type declarations that make large codebases manageable.

Nearly every shared hosting provider supports PHP out of the box, making deployment straightforward for web applications.

Pros: Ubiquitous web hosting support, massive ecosystem for web development, easy deployment, strong frameworks, continuous improvement.

Cons: Inconsistent standard library design, legacy codebases can be messy, reputation issues from older versions, less suitable for non-web applications.

TypeScript

TypeScript is JavaScript with static typing, developed by Microsoft and released in 2012. It compiles down to regular JavaScript but adds class-based OOP features and type checking during development.

The language brings traditional OOP concepts like interfaces, abstract classes, and access modifiers to the JavaScript ecosystem. Large frontend applications benefit from TypeScript's type safety, which catches errors before code runs in browsers.

Angular, one of the major frontend frameworks, is written in TypeScript. Many React and Vue projects also adopt TypeScript for improved maintainability.

Pros: Adds type safety to JavaScript, excellent tooling and IDE support, growing rapidly in popularity, works anywhere JavaScript works.

Cons: Adds compilation step to development, learning curve for JavaScript developers, configuration can be complex.

Swift

Apple introduced Swift in 2014 as a modern replacement for Objective-C in iOS and macOS development. The language combines OOP with functional programming concepts and emphasizes safety through its type system.

Swift eliminates entire categories of common programming errors through features like optionals, which force developers to explicitly handle the absence of values. The syntax reads clearly while maintaining high performance.

iOS developers have largely migrated from Objective-C to Swift for new projects. The language also works for server-side development through frameworks like Vapor.

Pros: Clean, modern syntax, strong safety features, excellent performance, official Apple support, growing server-side adoption.

Cons: Primarily limited to Apple ecosystem, frequent breaking changes in early versions, smaller community than JavaScript or Python.

Kotlin

JetBrains created Kotlin as a more concise alternative to Java that runs on the Java Virtual Machine. Google designated it as the preferred language for Android development in 2019.

Kotlin addresses many of Java's pain points with features like null safety, extension functions, and data classes. The language interoperates seamlessly with existing Java code, allowing gradual migration.

Android developers increasingly choose Kotlin for new projects. The language also works for server-side development, sharing code between platforms, and even compiles to JavaScript.

Pros: More concise than Java, excellent Android support, modern language features, full Java interoperability, growing ecosystem.

Cons: Smaller talent pool than Java, compilation can be slower, less mature ecosystem than established languages.

Other OOP Languages You May Encounter

The above are the top OOP languages. Yet, if you're exploring object-oriented programming (OOP), the OOP world doesn’t stop there. Many other languages embrace object-oriented principles, each offering unique features that created to different needs. Here are the additional object-oriented programming languages that support object-oriented principles.

JavaScript

JavaScript isn’t purely object-oriented, but it supports OOP through prototypes instead of traditional class-based inheritance. With modern updates (like ES6 classes), JavaScript now offers a more structured approach to OOP, making it essential for web development, especially in frameworks like React and Node.js.

Scala

Scala combines object-oriented and functional programming. It runs on the JVM and integrates smoothly with Java. Its expressive syntax and powerful type system make it a favorite for data processing and large-scale applications.

Dart

Dart, developed by Google, powers Flutter, a popular framework for cross-platform mobile development. It follows OOP principles, offering a clean syntax and performance optimizations that make building applications seamless.

Objective-C

Before Swift, Objective-C was Apple’s primary language for macOS and iOS development. It extends C with OOP features and dynamic runtime capabilities, making it flexible but more complex than Swift.

Perl

Perl supports object-oriented programming but allows both procedural and functional approaches. It is known for its flexibility and is often used in scripting, automation, and text processing.

Lisp & Common Lisp

Lisp, one of the oldest programming languages, has object-oriented features through the Common Lisp Object System (CLOS). It offers dynamic typing and flexibility, making it useful for AI and symbolic processing.

MATLAB

MATLAB is widely used in engineering and scientific computing. It includes OOP capabilities, allowing users to define classes and objects to manage complex mathematical models and simulations.

Smalltalk

Smalltalk is one of the earliest OOP languages, influencing many modern languages. It follows a pure object-oriented approach where everything, including numbers and functions, is an object.

R

R is an open-source programming language specialized for statistical computing and graphics. Widely used by data scientists and statisticians, its core strength lies in data analysis, offering extensive libraries and powerful tools for statistical testing, clustering, visualization (like pie charts and histograms), and reporting. It supports multiple OOP systems (S3, S4) and is cross-platform.

Each of these languages brings something valuable to the table, whether it's performance, simplicity, or flexibility. Choosing the right OOP language depends on your project, industry, and personal preference.

Which OOP Language Should You Choose?

Choosing an object oriented programming language is a strategic decision. It affects development speed, performance, long-term maintenance, and the overall direction of the project. Many developers look for the best object oriented programming languages for beginners, but beginners and teams benefit more from a language that matches real project requirements.

Below is a clear guide that explains how to pick an OOP language based on your goals, the project environment, and long-term plans.

Key Factors in Selecting an OOP Language

Choosing an OOP language is never a one-size-fits-all situation. These factors help guide the decision.

Project Requirements

Different projects require different strengths.
Below are simple examples that show how needs shape the choice:

• If speed and memory control are priorities, C++ supports high performance.
• If quick development and flexible workflows matter, Python or Ruby may support faster delivery.
• If the project targets enterprise platforms, Java provides stability and scalability.
• If the target involves modern web applications, JavaScript and TypeScript dominate the space.

Matching the best OOP languages to project needs ensures cleaner development and fewer issues down the road.

The Language Ecosystem

A language is more than syntax. It comes with an ecosystem of tools, frameworks, and libraries.

• Python has powerful libraries for AI, automation, and analytics.
• Java supports large enterprise applications with Spring and related frameworks.
• C# integrates smoothly with Microsoft technologies and .NET tools.

A strong ecosystem speeds up development, improves consistency, and reduces time spent solving common problems. An active community also provides documentation, tutorials, updates, and debugging solutions.

Team Expertise

Your team’s experience level matters.
If the team knows Python well and you force a switch to C++, productivity drops.
If the team has deep experience with Java and the project needs enterprise-level structure, sticking with Java produces faster results.

Learning a new language is possible, but time constraints can turn that learning curve into a risk. When deadlines matter, using a language the team already understands reduces errors and improves delivery speed. When long-term growth is the goal, teams can invest time in languages that support future scaling.

Integration with Existing Systems

Many systems interact with older components or industry-specific tools. Choosing a language that integrates smoothly reduces overhead.

Examples:

• Kotlin runs on the Java Virtual Machine, which makes it a natural choice for a Java-based environment.
• C# fits well into ecosystems that use Azure, Microsoft SQL, or Windows-based applications.
• Python connects easily with data platforms and scientific libraries.

A language that integrates cleanly saves time, avoids compatibility issues, and improves long-term stability.

Maintainability and Scalability

Clean code matters. Projects evolve, users grow, and features change. Some languages support structured, clear coding styles that age well.

• Java and C# encourage consistent object structures that help maintain modularity.
• Python supports readable syntax that improves collaboration and debugging.
• C++ provides fine control for systems that need detailed resource management.

A language that encourages organized code supports easier updates and long-term health.

Future Growth and Industry Trends

Technology changes fast. Choosing a language with a strong future ensures the project stays relevant.

Examples:

• JavaScript remains a core language for modern web development.
• Python continues to grow due to AI, automation, and data tools.
• Rust gains attention for performance and security benefits.
• Kotlin rises in popularity for Android development.

Tracking industry trends helps teams invest in languages with staying power. A language without active development or community support may limit growth later.

Quick Guidance Based on Common Needs

Best for beginners: Python offers the gentlest learning curve with readable syntax and immediate feedback. Java provides stronger fundamentals if you can handle more verbose code.

Best for enterprise: Java and C# dominate corporate environments with proven track records, extensive tooling, and large talent pools. Enterprise systems need stability and long-term support.

Best for web: JavaScript and TypeScript rule frontend development. Python, Ruby, and PHP each offer strong backend frameworks. Choose based on team expertise and project requirements.

Best for mobile: Swift for iOS, Kotlin for Android. Flutter with Dart works for cross-platform projects where native performance is not critical.

Best for high-performance systems: C++ delivers maximum speed and control for game engines, operating systems, embedded devices, and applications where every millisecond counts.

Consider your project goals, team skills, and deployment environment. Popular languages have more resources, libraries, and community support. Niche languages might offer specific advantages but come with smaller ecosystems.

Starting with one OOP language builds transferable skills. The concepts of classes and objects, inheritance, polymorphism, encapsulation, and abstraction apply across all these languages. Learning a second or third becomes easier once you understand the core principles.

Benefits of Using OOP Languages

Code organization — Classes and objects group related data and functions together, making large codebases navigable and logical.

Reusability — Write a class once, use it throughout your application or across multiple projects without rewriting functionality.

Maintainability — Changes to a class automatically propagate to all objects created from it, reducing update complexity.

Scalability — Add new features by creating new classes or extending existing ones without disrupting working code.

Productivity — Developers spend less time understanding code structure and more time implementing features.

These advantages become more apparent as projects grow. A small script might work fine with procedural code. A million-line application requires the structure OOP provides.

OOP also facilitates teamwork. Multiple developers can work on different classes simultaneously with minimal conflicts. Clear interfaces between objects define how components interact.

The principles of abstraction and encapsulation hide complexity. You use objects without needing to understand their internal implementation. This separation lets teams build large systems where no single person understands every detail.

Final Thoughts

Object oriented programming languages have shaped modern software development for good reason. They match how we naturally organize information and solve complex problems through decomposition.

Whether you choose Java for enterprise stability, Python for versatility, C++ for performance, or any other option discussed here, you're learning skills that apply across the technology landscape. The specific syntax varies, but the underlying concepts remain constant.

Different languages excel at different tasks. Pick the tool that fits your project rather than searching for one perfect language. Many professional developers work with multiple OOP languages throughout their careers.

S3Corp, a trusted IT outsourcing provider in Vietnam, has extensive experience building software with all major object oriented programming languages. Our teams deliver reliable solutions using Java, Python, C#, C++, and other modern technologies. Whether you need mobile apps, enterprise systems, or custom software, we apply OOP principles to create maintainable, scalable code.

FAQs

What are the main object oriented programming languages?

Java, Python, C++, C#, Ruby, PHP, JavaScript, TypeScript, Swift, and Kotlin represent the most widely used OOP languages today. Each serves different use cases but shares core OOP principles.

Is Python an OOP language?

Yes, Python fully supports object oriented programming with classes, inheritance, encapsulation, and polymorphism. Everything in Python is an object, though the language also allows procedural and functional programming styles.

Which OOP language is best for beginners?

Python offers the most beginner-friendly syntax and immediate feedback. Java provides stronger OOP fundamentals but requires more verbose code. Both are excellent starting points depending on learning style.

What is the difference between OOP and procedural programming?

Procedural programming organizes code as a sequence of instructions. OOP structures code around objects that combine data and behavior. OOP generally scales better for large, complex applications.

What are the four main OOP concepts?

The four pillars are encapsulation (bundling data with methods), inheritance (creating new classes from existing ones), polymorphism (using interfaces for different types), and abstraction (hiding implementation details).

Which languages support OOP?

Most modern programming languages support OOP to varying degrees. Java, C++, C#, Python, Ruby, PHP, JavaScript, TypeScript, Swift, Kotlin, Scala, and Dart all offer comprehensive OOP features.

What are some OOP examples in real applications?

Mobile apps use OOP to model user interfaces and data. Games use objects for characters, items, and environments. Web applications use classes for database models, controllers, and views. Banking systems use objects to represent accounts, transactions, and customers.

What are the advantages of OOP over other paradigms?

OOP provides better code organization, reusability, maintainability, and scalability. It models real-world concepts naturally and facilitates team collaboration on large projects through clear interfaces between components.